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README.md
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).images[0]
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gen_images.save('out_mid.png')
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```
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<a href="https://huggingface.co/Adapter/t2iadapter/resolve/main/figs_SDXLV1.0/res_depth_mid.png"><img width="480" style="margin:0;padding:0;" src="https://huggingface.co/Adapter/t2iadapter/resolve/main/figs_SDXLV1.0/res_depth_mid.png"/></a>
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).images[0]
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gen_images.save('out_mid.png')
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```
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<a href="https://huggingface.co/Adapter/t2iadapter/resolve/main/figs_SDXLV1.0/res_depth_mid.png"><img width="480" style="margin:0;padding:0;" src="https://huggingface.co/Adapter/t2iadapter/resolve/main/figs_SDXLV1.0/res_depth_mid.png"/></a>
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### Training
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Our training script was built on top of the official training script that we provide [here](https://github.com/huggingface/diffusers/blob/main/examples/t2i_adapter/README_sdxl.md).
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The model is trained on 3M high-resolution image-text pairs from LAION-Aesthetics V2 with
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- Training steps: 35000
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- Batch size: Data parallel with a single gpu batch size of `16` for a total batch size of `256`.
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- Learning rate: Constant learning rate of `1e-5`.
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- Mixed precision: fp16
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